Abstract :
A stochastic simulation model was used to study the
eects of the strength of prevailing wind (W), the size/
shape (Q) of sampling quadrats and their orientation in
relation to the prevailing wind direction (D) on spatial
statistics describing plant diseases. Spore dispersal fol-
lowed a half-Cauchy distribution with median dis-
tance l, which depended on simulated wind speed.
The relationship of spatial autocorrelation at distance k
(qk) to disease incidence (p) and distance was well
described by a four-parameter (a, b1, b2, b3) power-law
model; at a given p, qk declined exponentially with
distance. A total of 35 dierent quadrat sizes, ranging
from 4 to 432 plants, were used to sample the simulated
epidemics for estimating intraclass correlation (j). The
j-values decreased exponentially with increasing quad-
rat size; a binary power law model with three parameters
(a1, b4, b5) successfully related j to p. In general, the
eect of W and D was greatest on the parameters a, b1,
b2 and b3. The eect of W on a, b1, b2 and b3 depended
critically on the spatial pattern of initial infected plants
(Y); W had greatest eect for the random pattern. In
contrast, the main eect of D and its interaction with
W on the parameters a, b1, b2 and b3 were large and
consistent over dierent initial conditions. Variations in
a1, b4 and b5 were predominantly due to Y and Q. Only
for b5 under the clumped pattern was the eect of
W very large. For the parameters a1, b4 and b5 there was
a large interaction among W, Q and D for the clumped
and regular patterns. As expected, in general, the eect
of D increased with increasing prevailing wind strength,
quadrat size and quadrat length : width ratio. Using
square quadrats reduced signi®cantly the eect of W on
the parameters a1, b4 and b5; however, the eect ofWon
b5 was still very large for the clumped pattern. Sampling
perpendicular to the prevailing wind direction generally
resulted in larger dierences in the nine estimated
parameters.
